Python Flask image manipulation librery - python-3.x

I google it, but the number of library are overwhelming,
I'm looking for a image manipulation library, written in Python that I can implement in Flask;
I need to solve this simple sets of operations:
Upload the image.
Resize / scale the image (maintained the proportions).
Save the new image in a specific path with a specific name.
Remove the original image.
Also I notice that many promising project are unchanged in the last 2 years....

Related

How to redact texts in a pdf file in NodeJs

I am struggling to apply text redaction in a PDF file in a aws lambda function written in NodeJs. Here is a list of libraries that I have tried with no success:
pdf-lib: This library almost fulfils all the requirements except that it doesn't redact the text permanently as part of its limitations https://github.com/Hopding/pdf-lib/issues/827
PDF.js: To overcome the above limitation, tried to covert the pdf to an image, so the redaction black boxes are applied permanently. Example code here: https://github.com/mozilla/pdf.js/blob/master/examples/node/pdf2png/pdf2png.js However, this lib is not reliable as this cannot extract contents from most pdfs during the process.
Finally, Pdf2Pic: This library helps to overcome the limitation of the first library (pdf-lib) by the converting the pdf into images. But this library internally uses two non node based libraries (graphicsmagick and ghostscript) which I am trying to avoid.
Is there a nodejs based solution that can be used to apply redaction permanently on a pdf file or any solution that can be used to covert a pdf to images to overcome limitation of pdf-lib.

Azure Search - Highlights - Locating in image

Just looking for guidance or even a general outline on approach here.
I am using azure search to OCR a batch of pdfs. I have turned on hit highlighting and I am successfully getting results back there that I am looping through / displaying in my view for the end user. I was looking on expanding that functionality to show the pdf images with the highlighting on the images themselves like in the JFK azure example. I am not proficient in react and seem to be getting lost there.
I am assuming I need to save off the OCR images to a data store for reference using the normalized_images that are created? I do have pdfs locally I can load but assume the OCR images maybe different. Have turned on GeneratedNormalizedImagesPerPage and turned on cache which creates files in my storage account.
Then I assume I need to pull the associated image, display it, use the highlight results and pull a corresponding bounding box where the phrase was detected? Problem with that approach is that I do not see any association between the highlight hit and the location (bounding box) of the hit nor the associated image file the hit was on.
Probably way off on approach here but any guidance is appreciated.
Edit 1
I did noticed the items on this page in the JFK example: https://github.com/microsoft/AzureSearch_JFK_Files/tree/master/JfkWebApiSkills/JfkWebApiSkills
Would trying to replicate the ImageStore (so those are stored in my storage account) and then the HocrGenerator (appears to handle points in a doc) into my skillset for my index be the approach?
There are a few steps here:
you need to save the layoutText from the OCR skill somewhere the UI can access it. The JFK Files demo converts it to a HOCR (to display in the UI) and saves it in index as a field in the index so that it is retrieved in the search results. HOCR isn't necessary and you may find it more efficient to store the layout in blobs using a knowlege store object projection.
save the extracted images into blob storage using a file projection into the knowledge store. Keep in mind that the images may be resized in the process and the coordinates will match the resized image saved to the store. If you want to map the coordinates to the original image see this.
At search time, map the highlight to the the metadata. You will find this code in the nodejs frontend, however it may be simpler to follow in the original demo by following the code here. Essentially you just find the first occurrence of the highlighted word in the metadata, display the associated image, and calculate the bounding region of the word.

How to find custom logos from an image using nodejs

I am trying to find logo exists in an image or not, where i have create some logos list in png format.
I have tried using opencv with nodejs.
I have used OPENCV image-templating but I am not getting actual solutions.
Example:
I have some list of logos.
I have captured an image.
Not i have to detected in the image there is any logo exists or not.
have you tried training an ai to look at the logos you want to find or image recognition?

Retrieve original image after crop (cut)

I am doing a small program about using an image to calculate the Message digest, but what i also need to do is i need to put the another image into this original image, and put this modified image (original image embed by another image) to cloud.
There is my question that if i tried to download this modified image from cloud, and any way i can remove image which was embeded into original image, and using this original image to calculate to get Message digest the same as the original Message digest???
There are two ways i was trying to do, and i drew it through paper(maybe easy to understand what i am trying to say) below
Method 1
Method 2

node.js read images from PDF

I need to use PDF in a way similar to ZIP/RAR. To hold many images (ancient tibetan buddist literature), ideally 60000. But splitting in 10-100 volumes is OK.
Anything can be used for packing, but for unpacking we need Node.js. Because same PDF file must be served on web. But some users will need to use whole PDF.
So the question is, what node module I can use to read any single arbitrary image from huge PDF? Example would really help.
Every image is a single page. (Or in otherwords every page is single image)
We have been using https://github.com/mirkokiefer/Node-Magick for this....
But the pngs we get out sometimes are fairly low quality..

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